OVERVIEW:

Anticipating needs and proactively delivering information from social and device networks

PARC has been pioneering the research and development of post-personal computer information services through wireless networking, client-server architectures, and multi-device interaction. These two decades of research resulted in the invention of ubiquitous computing and context-aware services that anticipate a user's situation, proactively serve their information needs, and personalize recommendations.

We apply social and behavioral sciences to model human behaviors by fusing data from social, device, and information networks, as well as rigorous analytics and advanced machine learning techniques. Our privacy approach also extends beyond simple permissions settings; we uniformly preserve the anonymity of users through cryptographic analytic techniques.

We help our clients develop context-aware services that help people see more of what they need, suppress the "noise", and discover hidden relationships between people, information, and events. Most recently, we developed a contextual intelligence software platform which helps auto manufacturers provide a smarter, safer, and more personalized driving exprerience. [view video below | view press release on this topic]

applications

Automotive

Enterprise

Defense

Consumer

Smart, safe, personalized driving experiences

Recommendations

Infotainment services

Software for prioritized driver messages

Business intelligence

Customer relationship management(CRM)

Field service management

Task management

Workgroup awareness

After-action review

Mission planning

Situation awareness

Unit decision support

Location-based search

Loyalty & concierge services

Product recommendations

Media & entertainment

Health & wellness

Mobile payment

video

Contextual Intelligence for automotive

PARC Forum - "Context: the challenge... and the opportunities"

case studies

Consumer Case Study - Magitti

Making it easy to find things people like to do with friends

Young adults in Tokyo like to meet up at metro stations, but often don't seek out unfamiliar areas of the city. The "Magitti" mobile leisure activity recommendation system not only introduces young adults to new places, but also goes beyond simple location-based search by prioritizing listings about local restaurants, stores, movies, and other places according to the outdoor leisure activities users most likely want to do: dining, shopping, seeing shows, sports, and more. Magitti accomplishes this through a comprehensive personalization system which analyzes and incorporates actions and preferences. Even when users are familiar with an area, Magitti serendipitously discovers new things they like to do. Magitti was launched on the Japan iTunes store as "Machireco". [read more about this work and the client engagement]

Military Case Study

Providing real-time actionable information for small-unit operations

Unlike military operations in the past where large-unit (battalion and higher echelons) movements determined outcomes, today's military needs real-time information and decision support tools that enable small units and individual soldiers to decide among real-time alternatives: which targets to prioritize, what mission objectives are still attainable after enemy contact, and which objectives are highest-value intelligence sources. Manually entered information is time consuming, incomplete, and often inaccurate, limiting the intelligence value of dangerous missions. Mobile contextual intelligence allows soldiers to automatically detect significant events in the environment (gunshots, crowds) and tag them with contextual meta-data such as soldiers' motion and activities (walking, running, lying down, shooting). On-device analytics can warn soldiers when their patrol routes are becoming dangerously predictable, reducing the danger of ambush.